The present embodiments relate to correction of movement artifacts in a computed tomography image.
With the aid of computed tomography (CT), sectional images or slice images may be created with the aid of a computer and suitable image processing algorithms from a plurality of x-ray images or x-ray recordings (e.g., projections or projection images) that are recorded from different directions and over an angular range of more than 180° around the object. The grayscales of the sectional images essentially reflect the x-ray absorption coefficients of the irradiated material. Other names for computed tomography are CT scan or CAT scan, from computed axial tomography. In general, the aim of CT or x-ray image recordings is to record an image of an area under examination (e.g., a lung of an object under examination such as a human or animal patient). In such cases, the assumption is made that the object to be reconstructed does not move during the recording.
For computed tomography of living patients, this assumption may be incorrect, since the patient moves or the device does not perform the calibrated movement exactly but deviates from the movement. The results of these movements are image errors (e.g., movement artifacts) that may show as unsharp image areas or shadow images. For the correction or reduction of movement artifacts, movement-correction methods that are based, for example, on markers or specific features and that estimate the movement have been developed. Such a method has been presented by J. Wicklein, H. Kunze, W. A. Kalender, Y. Kyriakou in “Comparison of Image Features for Misalignment Correction in Flat-Detector CT,” Second International Conference on Image Formation in X-Ray Computed Tomography, Jun. 24-27, 2012, Fort Douglas/Olympic Village, Salt Lake City, Utah, USA.
In the feature-based methods, the movement of the object is estimated by minimization of a cost function. The entropy of the reconstructed object may be used as the cost function, for example.
From the literature (e.g., Y. Kyriakou, R. M. Lapp, L. Hillebrand, D. Ertel and W. A. Kalender, “Simultaneous misalignment correction for approximate circular cone-beam computed tomography,” 2008, Phys. Med. Biol. 53, pp. 6267-6289), it is known that by a global optimization of the geometry parameters, in which, for example, the detector offset is determined in relation to the focus position for all projections together, an improvement of the reconstruction results may be achieved. The optimization is undertaken for this purpose with the aid of a simplex algorithm. The disadvantage of this method is that more complex movements may not be compensated for.
Other approaches determine the movement with the aid of a projection-based method, which is insensitive to small movements, such as are typically present in applications in the neurological area. This provides that the corresponding area of application is restricted to these or similar problem areas. These methods also rely on features that have a significant effect on the projections.